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Performance Evaluation and Updates to a Geospatial Liquefaction Model Using Observational Data From the February 2023 Earthquake Sequence in Turkey and Syria

Description: 

Geospatial ground failure models are routinely implemented as part of the Ground Failure tab of the USGS Event page. After the February 2023 Earthquake sequence in Turkey, ground failure maps were disseminated for the Mw7.8 and Mw7.5 events. In addition to the Zhu et al. (2015) and Zhu et al. (2017) models, the authors have an updated geospatial liquefaction model for the region (Zhan et al., 2023) and have developed an estimate of model uncertainty for the Zhu et al. (2017) model. Reconnaissance reports from the earthquake sequence have identified numerous observations of liquefaction with many observations in the port city of Iskenderun and in Gölbaşı, especially along Gölbaşı Lake. In addition to field liquefaction observations, we will analyze pre and post SAR image pairs and interferometric phase information to determine whether liquefaction deformations can be detected. In this poster, we will present the geospatial liquefaction model predictions from the three models with georeferenced observations. We will evaluate performance of the three models and provide recommendations on regional specific updates. Geospatial liquefaction models can be divided into liquefaction susceptibility and event specific components. Using Bayesian sequential learning, we will demonstrate a regional model updating method that can be used to improve performance of geospatial liquefaction models by updating the susceptibility component of the model for that region.

Session: February 2023 Mw 7.8 Earthquake Sequence in Turkey [Poster]

Type: Poster

Date: 4/19/2023

Presentation Time: 08:00 AM (local time)

Presenting Author: Laurie G. Baise

Student Presenter: No

Invited Presentation: 

Authors